CEU, Economics Department

Lecturer: Herbert Gintis
Course: 2 credits

Evolutionary Game Theory provides an in depth study of dynamical systems and their relationship to dynamical principles in
game theory. We study evolutionarily stable states and their relationship to Nash equilibria. We use classical dynamical
systems theory to study the nature and stability of critical points in evolutionary dynamical systems, and we use Mathematica
and agent-based modeling to analyze the properties of complex, nonlinear dynamical systems arising from strategic
interaction. We then study Markov processes and stochastic dynamical systems. We close the course with Bayesian
game theory and Signaling Games, stressing the endogeneity of beliefs and the coevolution of signaling systems and
genetic systems.

Course Structure:

 Evolutionarily Stable Strategies: Game Theory Evolving, Chapter 9

 Dynamical Systems: Game Theory Evolving, Chapter 10

 Evolutionary Dynamics: Game Theory Evolving, Chapter 11

Evolutionary Dynamics: Mathematica

Evolutionary Dynamics: Solving Problems

Stochastic Dynamical Systems: Game Theory Evolving, Chapter 12

Bayesian Games: Game Theory Evolving, Chapters 13,16

Signaling Games: Game Theory Evolving, Chapter 14